Monday, June 30, 2014

Alternate history novels have been very popular over the last few years. So surely there must be a market for alternate history maps. Newcastle Brown Ale obviously think so.

The brewer has released an alternate history map of the United States in honor of Independence Day. If We Won is a brilliant map of the USA showing how the country might look if the American War of Independence had been won by Great Britain.

Enter any town or city into the map and you can discover what the location would be named if the Americans hadn't been so unhappy about paying a little tax. For example El Paso becomes Ye Olde Paso, Charlotte becomes North Charlottesvilleford and San Francisco becomes Wolverhampton.

Even if the thought of a USA still under the thumb of Great Britain turns your stomach it is worth visiting the map just to check out the gorgeous custom map tiles.

One of the great features of the Leaflet mapping library is that you are able to choose from a number of available base map tiles. Today I was searching for a good base map layer for a project which I'm currently working on. Luckily I came across a great map which allows you to view a large number of available map tile layers that can be easily added to a Leaflet map.

Leaflet Providers Preview provides views of a number of OSM, MapQuest, Stamen and other map layers within a Leaflet map. The map even includes a JavaScript snippet for each layer so you can just cut and paste the code into your own Leaflet map.

Unfortunately this map doesn't include the most important map tile layer for Leaflet - the Guild Wars 2 map layer. I therefore decided to quickly create my own little Map Tiles for Leaflet Map. My map has nowhere near as many map layers as the Leaflet Providers Preview but it does include the Pelagios Roman Empire Digital Map tiles and the all important Guild Wars 2 map. If you want to use these map tiles in your own Leaflet maps you can view the code or click on the links in the map layer's attribution.

Late last year Pharrell Williams released a 24 hour video of his song Happy. You can watch the video at 24 Hours of Happy. When you visit 24 Hours of Happy you are dropped into a position in the video based on your local time. However you can use the stop-clock control to navigate to any point within the 24 hours of the video.

One result of the video was that people around the world decided to make their own Happy videos. We Are Happy From is an Esri map featuring these global video responses. Click on a marker on the map and you can watch people around the world getting down to Pharrell's Happy song.

The Nike+ Places map has an informative heat map layer which shows the most popular running routes for owners of Nike's running app and tracking devices.

Using the heat map layer you can search for the most popular running routes in any location around the world. In truth the popular routes revealed by the heat map layer won't come as a great surprise. Parks and off-road routes seem to be very popular with joggers. For example in London the major parks and canal tow paths prove very popular with runners.

Strava has also created a handy heat map of the most popular running routes of its users. In New York joggers love to run in Central Park and along the southern tip of Manhattan.
In Chicago the lake shore is very popular and in San Francisco the
Golden Gate Park and The Embarcardero seem to be the most popular places
for joggers.

The Strava Global Heatmap
is a Google Map of where joggers like to run and
where cyclists love to ride. The map allows you to view the most popular
running and cycling routes by Strava users across the world.

If you don't believe the Strava and Nike data you can cross now cross check it with Runkeeper data. Mapbox has released a worldwide map of 1.5 million walks, runs, and bike rides undertaken by Runkeeper users.

The 1.5 Million Walks, Runs, and Bike Rides
map overlays Runkeeper routes on top of Mapbox's terrain layer. The map
includes some quick links to jump to the map of a few major cities
around the world but you can pan and zoom the map to view the popular
running routes at any location in the world.

Sunday, June 29, 2014

A God in Every Stone
is a novel by Kamila Shamsie. To accompany the publication of the novel
Kamila has released a gorgeous interactive map featuring some of the
important locations in the novel. The novel takes place in the early
20th Century. However artifacts and events from the Persian Empire impinge on the plot and the interactive map reflects this with three different maps representing different eras of history.

The map uses the Google Maps API and the Leaflet mapping library with
some gorgeous custom map tiles. I love the fading in and out of the
different custom map tiles on the map. Use the links at the bottom right
of the map to switch between the map tiles. Clicking on the markers
also switches the map tiles when they relate to a particular era covered
in the novel.

There are some interesting experiments going on displaying 3d building views with OpenStreetMap data. Mapzen's new Vector Tiles map demo shows building footprints at lower zoom levels and some impressive 3d buildings when you zoom in on the map.

The map includes a number of controls to change the perspective of the
map view, to change the lighting effects and to add various effects to
the map (check out the 'elevator' view). You can import the 3d buildings into your own maps by using the Mapzen Vector Tile Service API.

Visits
is a neat way to visualize your Google location history or Flickr
albums as a mapped timeline. Add a link to your Google location history
or a geotagged Flickr album and you can immediately create an impressive
mapped timeline.

A chronological series of circular static Google Maps creates a visual
timeline of your check-ins or photos. Mouse-over any of the circular
maps and one line is drawn from the map to its date in the timeline and
another line appears to show its location on a larger map.

You can control the look of your timeline visualization by selecting a
date-range. You can also control the level of zoom in the circular maps
by selecting from Street, Neighbourhood, City, Region, or Country views.

Martin Raifer has released a beautiful map of OpenStreetMap Node Density. The map provides a general overview of OpenStreetMap's global coverage.

Each pixel on the map shows the number of nodes at that location. When comparing areas on the map you need to carry out a sort of population normalization calculation in your head. For example central Australia appears darker on the map than some of the Australian coastline. This is more than likely due to the fact that urban conurbations are mainly on the coast and therefore there will be more map features than in the less densely populated areas in the middle of Australia. You also need to remember that the map uses a Web Mercator projection and therefore this makes it more difficult to compare locations at different latitudes.

In Europe the Netherlands seems to have the highest node density. Is this because the Netherlands has a huge number of OpenStreetMap contributors or just a reflection of the relative urban density of the country? In the USA California shines out, particularly central San Francisco and Bakersfield. My guess is that Bakersfield in particular must have a pretty dedicated team of OpenStreetMap contributors.

The mosaic of 43,634 pictures of Detroit houses is a very effective method to convey the sheer scale of the problem facing many Detroit homeowners.

It's possible that the New York Times gave the job of hunting out the Street View images of 43,634 properties to one of their interns. However it is more likely that the Times used the Google Maps API to geocode the addresses and then used the latitude and longitudes to return the static Street View images of the houses from the Street View Image API.

This isn't as easy as it sounds. If you just enter a latitude and longitude into the Street View Image API you will get a random facing Street View from that location. To actually retrieve the Street View image of the desired house you also need the correct heading to tell the API which direction to look.

Herein lies the problem. How do you quickly retrieve the correct heading for 42,623 addresses to ensure that your Street View images are all facing in the correct direction. One solution is to use the Google Maps API to find the nearest available Street View to the address and then use the computeHeading (from: LatLng, to:LatLng) function to calculate the correct heading (the two LatLngs being your nearest available Street View latitude and longitude and the latitude and longitude of your address).

I can't find a good map that demonstrates this function in action - in order to show the Street View of a house. However this Point the Street View to a Marker demo uses the exact same principal to find the correct heading to show a Street View looking towards a marker on a map.

Earlier this week Google Maps Mania featured the Wellbeing Map Explorer, a map showing how people subjectively rate their well-being in different English regions. The OECD has also been mapping well-being.

The OECD measured regions around the world in eight different areas – income, jobs, health, access
to services, environment, education, safety, and civic engagement. A
score was given to each region in each area.

The OECD Regional Well-Being map provides a mapped interface to explore the results of the OECD well-being assessments. Using the map you can not only explore the well-being results for 300 regions around the world but you can compare the results of different regions.

If you select a region on the map you can view the region's well-being scores in each of the eight categories and you can also view a list of other regions which have similar well-being scores. For example California has similar well-being scores to the Basque country in Spain and New York state has similar scores to Greater London in the UK.

The OECD has also mapped how people around the world subjectively view their well-being.
The OECD's Better Life Index
is an attempt to measure the importance people around the world give to
different factors essential for their well-being. It is a survey
designed to measure the importance people in different countries give to
11 topics about their quality of life and material living conditions.
The OECD has also released a map which visualizes the results of the survey
by country.

Each country's marker is colored to reflect the highest rated topic by
respondents to the survey in that country. The markers are also sized to
show the number of responses from each country. You can mouse-over the
markers to view the highest rated topic for each country. If you click
on a marker you can view more details about the selected country's
results, including the number of responses by gender and age and the
ratings given to each topic.

The map includes a useful 'stories' feature which, when selected, zooms
in on interesting results from the survey shown on the map.

Friday, June 27, 2014

Visits is a neat way to visualize your Google location history or Flickr albums as a mapped timeline. Add a link to your Google location history or a geotagged Flickr album and you can immediately create an impressive mapped timeline.

A chronological series of circular static Google Maps creates a visual timeline of your check-ins or photos. Mouse-over any of the circular maps and one line is drawn from the map to its date in the timeline and another line appears to show its location on a larger map.

You can control the look of your timeline visualization by selecting a date-range. You can also control the level of zoom in the circular maps by selecting from Street, Neighbourhood, City, Region, or Country views.

The National Library of Scotland has released interactive maps of 307 trench maps from World War I. The maps not only show the location of First World War trenches but reveal the location of enemy positions and defences.

A New York Times feature, The Great War: A 100-Year Legacy of World War I examines the lasting effects of WWI around the world through a series of articles. It also includes links to view some of the New York Times articles published during the war in the amazing New York Times Times Machine archives.

The whole feature is headed by an interactive map which allows you to view the map of Europe before and after WWI and the map of Europe as it looks today. These three views allow you to view how the country borders of Europe looked before the war, how they changed immediately after World War I and how the map of Europe looks in 2014.

One hundred years ago tomorrow the Archduke Franz Ferdinand of Austria was assassinated, setting off a chain of events which eventually led to World War, the death of millions of people and the map of Europe changing forever.

Radio Free Europe Radio Liberty has created a neat mapped visualization which allows you to compare the 1914 map of Europe to the 2014 map of Europe. Europe 1914 and 2014 allows you to compare the two maps and view how the map of Europe has changed dramatically over the last one hundred years. Swipe to the left to reveal the 1914 map and swipe to the right to view the 2014 map.

As you swipe to reveal the 2014 map you can can say goodbye to the German, Austro-Hungarian, Ottoman and Russian Empires and say hello to Poland, Finland and a number of other new countries in Eastern Europe.

Thursday, June 26, 2014

I love CartoDB's Torque library but if I see one more Twitter map of a World Cup game I think I might explode. I think we get it now - people Tweet a lot when someone scores a goal. Torque is a very powerful visualization tool for animating large time-stamped data steps on an interactive map. It really does deserve to be used in better mapped visualizations.

Ramadan: How the World Celebrates might be another Torque / Twitter map but it does add a few new interesting tweaks to the usual Torque powered Twitter visualizations. In 2013 74.2 million Twitter messages were sent around the world mentioning Ramadan. This map animates through the Tweets actually sent during Ramadan itself.

What I like most about Ramadan: How the World Celebrates is that it isn't just a meaningless playback of Twitter activity overlaid on a map. Instead it actually attempts to analyse some of the cultural differences gleaned from the data by looking at the language and words used in different countries and regions.

During the animation the map zooms in on different areas of the world and reveals some interesting contextual information about the sort of messages sent in different areas. For example, in the USA the long summer days mean that a lot of Muslims send messages about how hungry and thirsty they are. In Turkey 'May you be in good health' is a popular message. While in Paris and Saudi Arabia, after the sun sets, many Muslim Twitter users mention the dates that they are eating.

A Plane Spraying a Rice Field in Southern Spain deserves a mention as well, simply because it is a Torque powered visualization that doesn't use Twitter data and doesn't mention football. This Torque powered map (actually it seems to be missing a map) animates the GPS track of a plane taking off from a landing strip, spraying a rice field, landing, refueling, taking off again, spraying again and returning to a landing strip.

I've no idea if this uses a real GPS track or is just a demo map of how crop spraying works but it is a simple and neat demonstration of a crop-spraying flight pattern.

I like this simple and understated map of Berlin swimming lakes and swimming pools. Berliner Badenstellen shows the locations of outdoor swimming locations and indoor swimming pools in and around the German capital.

The use of earthy natural tones on the map complements the map's focus on where you can swim in nature in Berlin. The sparing use of only two 3d buildings on the map also helps by not overwhelming the map with visual noise. The choice of two of Berlin's most recognized landmarks, the Berliner Funkturm tower and the Berliner Fernsehturm tower, provide enough geographical context for the user without distracting attention from the swimming lake markers.

If you select a marker on the map you can get brief information on the depth and the water quality available at that location.

Wegbeeld is a map of traffic conditions on the Netherlands' motorway network. The map allows you to replay the last three hours of traffic on the whole network. So you might say that this map includes reel-time as well as real-time traffic conditions.

The map includes an estimation on the current CO2 emissions being generated by all the cars on the Netherlands' motorways. The estimation is calculated based on the amount of traffic and the average speed of all the cars on the road.

The use of an animated road layer works really well in highlighting the important data on the map. The map itself is derived from PDOK, the Dutch governments digital maps and geodata department.

Wednesday, June 25, 2014

TransitMe uses the Google Maps API to provide interactive maps of a number of transit systems around the world. Using TransitMe you can now zoom in and pan around the transit maps for a number of worldwide cities.

Currently the transit maps of New York, London, Paris, Madrid, Seoul and Shanghai are available on TransitMe.

If you are wondering why TransitMe doesn't overlay these transit maps on top of the underlying Google Maps road map layer then you should have a look at the the Actual New York MTA. Ben Schmidt has taken the transit maps of New York, Boston and Washington DC and then stretched,
squeezed and rotated them so that they fit onto a Web Mercator map of New
York.

The MTA Map of Actual New York helps to highlight the geographical inaccuracies common to transit maps. For example in New York the MTA map expands Manhattan, due to the higher proportion of lines and
stations situated there. You have to admit that the map does lose some
legibility when you squeeze all that information onto a more
geographically accurate map.

Stonehenge in your City can help you find nearby streets which are aligned with the sunrise or sunset on the winter or summer solstice. The site has mapped out hundreds of cities around the world highlighting the streets which face towards sunrise or sunset during either solstice.

Streets which point towards sunrise are marked in yellow on the map and the streets which align with sunset are marked in red.

We have only just passed the summer solstice so you could use the map to capture your own Manhattanhenge moment. Twice a year the setting sun aligns
with the east–west streets in Manhattan in New York City, providing a great photo opportunity for anyone who wants to snap the sun setting/rising at the end of a Manhattan street. You could use this map to capture a sunset or sunrise at the end of one of your local streets.

NYCHenge
is a CartoDB map that allows you to find the direction of the sunset
for any location in New York for any day. The east-west facing streets
in New York's grid pattern are displayed in red on the map and the
direction towards the sunset is displayed with a white poly-line. It is
therefore a simple matter to find your location on the map and find out
if the direction towards the sunset aligns with a specific street.

VeloViewer
has created an interactive map that allows you to view the road
orientation for any district or city in the world. Using the map you can
zoom in on any area of the world and a rose diagram displays the road
orientation distribution within the current map bounds.

The map uses the underlying data for roads in OpenStreetMap to calculate
the road direction patterns on the fly. This means that you can move
the map around and zoom in or out on any location and the rose diagram
will update to show the road direction distribution within
the current map view.

If you live in England and you want to be happy then you should move to Rutland. The Wellbeing Map Explorer is a map showing how people subjectively rate their well-being in different English regions.

The map allows you to view the Office for National Statistics Annual Population Survey results for three different questions: Happy Yesterday, Life Satisfaction and Worthwhile. The map is fairly clear - if you want to be happy you should avoid living in a larger city and if at all possible you really should move to Rutland.

Tuesday, June 24, 2014

A God in Every Stone is a novel by Kamila Shamsie. To accompany the publication of the novel Kamila has released a gorgeous interactive map featuring some of the important locations in the novel. The novel takes place in the early 20th Century. However artifacts and events from the Persian Empire also impinge on the plot.

The map uses the Google Maps API and the Leaflet mapping library with some gorgeous custom map tiles. I love the fading in and out of the different custom map tiles on the map. Use the links at the bottom right of the map to switch between the map tiles. Clicking on the markers also switches the map tiles when they relate to a particular era covered in the novel.

We do like mapped data visualizations at Google Maps Mania. Too often however these visualizations aren't really much more than pretty looking maps. Too often they lack any real analysis of the data displayed.

This week I've seen two interesting examples of gender mapping. This strikes me as an area that is ripe for serious analysis.

Geotheory has been looking at UK census data and mapping the male / female composition of urban workplaces. Gender in Urban Workplaces shows that in the UK there are some clear areas of discrimination. In London in particular the financial districts clearly employ far more men than women. In west-central London (where the shops are) women make up a far greater proportion of the workforce.

In the United States BuzzFeed has been mapping male and female usage of the bike sharing systems in New York, Chicago and Boston. The maps identify the gender balance of bike stations in each of the cities.

The data not only shows which stations are least used by women it also reveals that the percentage of women using the bike sharing networks increases at the weekend. This suggests that women are far less likely to commute by bike than men. One possible reason is that women 'trip-chain' more than men. While men can simply commute to and from work, women are tasked with dropping off kids on the way to work and picking up the groceries on the way home.

I've recently become enamored with the 'neon' map style that is being used in a lot of mapped visualizations of large data sets. I decided this morning to see if I could create a neon route on a map which actually flickers like a real neon light.

It turns out it is possible by using setTimeout to continuously loop through different colored polylines on the map. Here is my Neon Polyline map (obviously the still screenshot above doesn't show the flickering effect).

In reality the effect is quite annoying so I don't think I would ever use this to highlight a route on a map. However if you set the setTimeout value to one or two seconds you get a slow flashing effect rather than the flickering line. I think that the flashing line is quite effective and could be used to highlight a route on a map.

The neon flickering effect is less annoying when you zoom out on the map. I therefore think it could be used to create a neon flickering marker on a map. Here is a Neon Marker example, which uses a flickering neon style marker to show London on a map of the world.

Monday, June 23, 2014

NYC Taxi Tiles is a map of 2013 New York City taxi data. The data for the map was obtained through a FOIL request (you can read the interesting story behind the request here). The blue dots on the map represent pick-up points and the yellow points show drop-off points.

I've been seeing a lot of these 'neon' style maps lately. These maps share some common features, such as dark or grey-scale map tiles and the data overlaid with lighter dots or lines. The name of this particular map provides a clue as to how these maps are created - with the data processed and added to the actual map tiles rather than being added in the browser.

It should be possible to load smaller amounts of data to the map in the browser. I like this Moscow Hills OpenStreetMap of Moscow, using gradient colored roads to show
elevation levels throughout the city. As well as using the color of the
roads as a guide you can mouse-over any point on a road to view the
elevation at that point.

I think again the data is actually a part of the map tiles rather than being overlaid on top of the map. Theoretically however you could use the Google Maps API
and the Elevation Service to create a map with the data being loaded in the browser. In fact it should be fairly simple to draw a gradient polyline along a road using the Stroke Style feature with the Google Maps SDK for iOS. Unfortunately gradient polylines have yet to be added to the Maps JavaScript API.

The Strava Global Heatmap
is a really informative Google Map of where joggers like to run and
where cyclists love to ride. The map allows you to view the most popular
running and cycling routes by Strava users across the world.

The different colored neon lines (for the different Strava activities) appear to be added as map tile overlays. It makes sense to pre-process the data in this way rather that try to generate millions of data points in the browser.

Mapbox has created a similar map using Runkeeper data. This map shows 1.5 million walks, runs, and bike rides undertaken by Runkeeper users.

The 1.5 Million Walks, Runs, and Bike Rides
map includes some quick links to jump to the map of a few major cities
around the world but you can pan and zoom the map to view the popular
running routes at any location in the world.

1.5 millions tracks is a lot of data for the browser to process. With this amount of data it seems common sense to create map tiles with the data and create a mapped visualization with your custom mapped tiles.

The New York Daily News has mapped five years of crimes reported at New York subway stations. How Safe is your Subway? uses scaled circular markers to visualize the number of crimes committed at each stop on the MTA network. The map shows crime recorded over a five-year period, from July 2008 to June 2013. You can filter the map to visualize different types of crime on the New York subway system.

One of the biggest mistakes made by a lot of mapped data visualizations is to not normalize data by population (or in this case passenger numbers). The Daily News map doesn't make this mistake and gives you the option to view the number of crimes normalized by the number of trips made. For example, you would expect a busy station such as Times Square to have a proportionally higher number of recorded crimes than less busy stations simply because it has far more traffic.

Being able to view the rate of crimes per 100,000 trips allows you to compare the crime-rate at different stations based on the number of passengers.

CrimeDC is a new crime map for Washington DC created by the DC Police Union. The map allows you to view crimes committed in DC's neighborhoods by type of crime and by different time ranges over the last 12 months.

One neat feature of the map is that each neighborhood is shaded on the map to give an overview of whether crime has fallen or risen in the last month. Select a neighborhood on the map and you can view the percentage change in crime from the previous month and also view a chart of the frequency of crimes in the neighborhood over the last few years.

There are some interesting experiments going on displaying 3d building views on OpenStreetMap. Mapzen's Vector Tiles map demo shows building footprints at lower zoom levels and 3d buildings when you zoom in on the map.

The map includes a number of controls to change the perspective of the map view, to change the lighting effects and to add various effects to the map (check out the 'elevator' view).

OSM Buildings is a pretty awesome JavaScript library for visualizing OpenStreetMaps building geometry on interactive maps. Check out this Building Shadows demo to view an example map which includes 3d buildings and building shadows which are dependent on the date and time of day.

The map includes two slide controls to adjust the position of the sun by the time of day and by the time of the year.

F4map
is an amazing 3d map built with OpenStreetMap data. The map includes some
incredible 3d buildings, 3d trees and even the water is animated. The
shadows on the map are in real-time and reflect the position of the sun
and therefore move throughout the day.

Use the ctrl key with the up and down arrow keys on your keyboard to change the angle of the map.

Sunday, June 22, 2014

One of the most interesting uses of Street View imagery since its introduction on Google Maps has been by MIT. MIT's Place Pulse
project is a crowd-sourced experiment examining people's perceptions of
different urban environments using their reactions to different Street View images.

MIT has now taken the the crowd-sourced safety rankings for 3,000 street images from
New York and Boston and created an algorithm to automatically create a
perceived safety rating for Street View images. Using the Place Pulse
scores MIT assigned attributes to features present in the images,
associated with the image's textures, colors and shapes. They then used
machine learning to associate image features with scores of perceived
safety. MIT can then use the resulting algorithm to predict the
perceived safety of a new image. They can therefore give any Street View
image a 'StreetScore' based on the results of the Place Pulse survey.

StreetScore has
now released a number of maps showing areas of perceived safety in New
York, Boston, Chicago and Detroit. Using Street View images of the city
StreetScore assesses the perceived safety of locations throughout the
city. Green dots on the map represent the areas which StreetScore has
assigned as having a high perceived safety rating and the red dots are
the locations with a low perceived rating score.

BikeDistrict
is a really great example of providing bike directions on an
interactive map. The application allows you to search for and get
cycling directions in Milan, Italy.

The application returns three suggested routes for any directions query:
'cycle', 'direct' and 'safe'. The 'cycle' option returns a route which
preferences cycle paths and avoids the roughest roads. Milan has a lot
of cobbled streets and selecting the 'cycle' route will return a route
which tries to avoid these cycle unfriendly roads. The 'direct' option
returns the most direct route and the 'safe' option will avoid the busiest streets and preference cycle paths.

The staged directions for each route are color coded on the map and in
the step-by-step instructions to highlight the road conditions for every
stage of the journey. If you don't like a particular road in the
suggested directions you can select it on the map and BikeDistrict will
automatically route around it.

As well as providing bike directions BikeDistrict can show the location
of all bike stations (with real-time information on the number of bikes
and docks available), bike parking locations, drinking fountains, bike
repair shops and biking related events.

In the UK all the single people live in London, all the cyclists live in
Cambridge & Oxford and all the old people live on the coast.1

I gleaned these nuggets of information from DataShine Census,
a new census data explorer for the UK. A census map which I would be
quite happy exploring all day. I've seen a lot of maps of census data
over the years and I must say that this new map from DataShine ranks
right up there among the best.

DataShine Census maps data from the 2011 UK census. What I really like
about DataShine is the amount of data from the census that has been
mapped. You can explore the data down to census tract level in a number
of different demographic categories, including population, housing,
education, employment and beliefs. Each of these categories include a
number of sub-categories, so there really is a lot of data to explore on
the map and a lot that can be learned about the UK and its people.

Footnote:

1 All the misreadings of the data here are the fault of the author and not the fault of DataShine Census.

Saturday, June 21, 2014

MIT has released a number of maps showing areas of perceived safety in New
York, Boston, Chicago and Detroit. Using Street View images of the cities StreetScore assesses the perceived safety of locations throughout the
city. Green dots on the map represent the areas which StreetScore has
assigned as having a high perceived safety rating and the red dots are
the locations with a low perceived rating score.

One thing missing from the MIT StreetScore maps is the ability to filter the results shown on the map by score. However MIT has made the data available for download so I decided to make my own map of New York and add some filters.

In this Safe New York map I've taken the data for Manhattan, New York. The map shows the safest and least safe locations as perceived by the MIT Street View algorithm. The MIT q-score assigns a value up to 43 for each Street View image. The higher the q-score assigned the higher the safety perception. The lower the q-score the lower the safety perception.

I've marked every location which has a score under 15 with a red marker and every location with a score over 30 with a green marker. All locations with a score between 15 and 30 are displayed with a yellow marker.

You can filter the markers shown on the map by using the four buttons in the map sidebar.

I think there is some value in being able to query the data in this way. Switching between the highest rated and lower rated locations on the map (green & red buttons) is quite effective in identifying areas where there are clusters of locations perceived as unsafe and with few safe areas.

For example Hunts Point and Wards Island can be clearly identified as areas that are perceived unsafe by the MIT algorithm. It also becomes clear by just looking at the lowest (red) scores that major roads are often perceived as unsafe.

Using the Google Maps API also means that you can use Google Maps Street View. You can drag and drop pegman onto the map to check out the Street View images for any location. Therefore if you are wondering about why a particular area has been given low scores you can check out the Street View imagery for yourself and make your own judgement.

Friday, June 20, 2014

In New York joggers love to run in Central Park and along the southern tip of Manhattan.
In Chicago the lake shore is very popular and in San Francisco the
Golden Gate Park and The Embarcardero seem to be the most popular places
for joggers.

The Strava Global Heatmap
is a really informative Google Map of where joggers like to run and
where cyclists love to ride. The map allows you to view the most popular
running and cycling routes by Strava users across the world.

If you don't believe the Strava data you can cross now cross check it with Runkeeper data. Mapbox has released a worldwide map of 1.5 million walks, runs, and bike rides undertaken by Runkeeper users.

The 1.5 Million Walks, Runs, and Bike Rides map overlays Runkeeper routes on top of Mapbox's terrain layer. The map includes some quick links to jump to the map of a few major cities around the world but you can pan and zoom the map to view the popular running routes at any location in the world.

The City of New York has adopted over 150 urban renewal plans since 1949. Over the years areas of the city have been selected for renewal because they have been designated blighted or obsolete. The city then gets federal funding for purchasing the land, moving the residents out, demolishing the structures and making way for new public and
private development.

Urban Reviewer has mapped the locations of all the urban renewal plans in New York. The areas affected by the urban master plans are highlighted on the map. If you select a highlighted plan on the map you can view the original map of the plan and select individual lots within the plan to view the intended use of the lot under the planned renewal.

The map includes a date control which allows you to filter the plans shown on the map by date. It also comes with a number of search filters, which make it possible to filter the plans shown on the map by mayoral administration and by planned use. It is also possible to highlight on the map all the lots which have remained vacant.

The Pulitzer Center has created an informative map of global child mortality rates to highlight the progress the world has made in helping children survive their early years. The Child Lives map uses UNICEF data with the Mapbox platform to create a powerful visualization of the improvements in child mortality rates across the world.

The use of scaled circular markers provides a global overview of the child mortality rates in each country. Switching between the two dates, 1990 and 2012, provides a quick visualization of how child mortality rates have fallen across the globe during these years.

You can analyse the data in more depth by selecting individual countries on the map. This allows you to view the percentage reduction in under-five mortality rates in the selected country since 1990. You can also view two charts showing the number of deaths per 1000 live births and the total number of under five deaths for the years 1990 to 2012.